Machine-learning methods are being actively developed for computed imaging systems like MRI. However, these methods occasionally introduce false, unexplainable structures in images, known as hallucinations, that can lead to incorrect diagnoses.
Category: Cloud Computing
A new study shows that deep learning models trained on large sets of cancer genetic and tissue histology data can easily identify the institution that submitted the images.Read More
A number of vulnerabilities, known collectively as deep learning adversaries, hold artificial intelligence back from its full potential in applications like improving medical imaging quality and computer-aided diagnosis. Researchers at Rensselaer Polytechnic Institute are seeking to combat this.Read More
As artificial intelligence (AI) becomes increasingly integrated into clinical practice, the Radiological Society of North America is launching its Imaging AI Certificate program to deliver a pathway for radiologists to understand and learn how to apply AI to their radiology practices.Read More
Researchers have developed an artificial intelligence-based brain age prediction model to quantify deviations from a healthy brain-aging trajectory in patients with mild cognitive impairment, according to a study published in Radiology: Artificial Intelligence.Read More